Instructions to use MMG/mlm-spanish-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMG/mlm-spanish-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MMG/mlm-spanish-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MMG/mlm-spanish-roberta-base") model = AutoModelForMaskedLM.from_pretrained("MMG/mlm-spanish-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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To test the quality of the resulting model we evaluate it over the [GLUES](https://github.com/dccuchile/GLUES) benchmark for Spanish NLU. The results are the following:
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| XNLI | 71.99 (accuracy) |
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| Paraphrasing | 74.85 (accuracy) |
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To test the quality of the resulting model we evaluate it over the [GLUES](https://github.com/dccuchile/GLUES) benchmark for Spanish NLU. The results are the following:
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| Task | Score (metric) |
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| XNLI | 71.99 (accuracy) |
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| Paraphrasing | 74.85 (accuracy) |
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